Local singularity and S–A methods for analyzing ore-producing anomalies in the Jianbiannongchang area of Heilongjiang,China

The Heilongjiang Jianbiannongchang area is located at the confluence of the Great and Lesser Xing’an Ranges.This area has a complex magmatic and tectonic evolutionary history that has resulted in a complex and diverse geological background for mineralization.In this study,isometric logarithmic ratio(ILR)transformations of Au,Cu,Pb,Zn,and Sb contents were performed in the1:50,000 soil geochemical data of the Jianbiannongchang area.Robust principal component analysis(RPCA)was conducted based on ILR transformation.The local singularity and spectrum-area(S-A)methods were used to extract information on mineralogic anomalies.The results showed that:(1)the transformed data eliminated the influence of the original data closure effect,and the PC1and PC2 information obtained by applying RPCA reflected ore-producing element anomalies dominated by Au and Cu.(2)The local singularity method can enhance the information of the local strong and weak slow anomalies.After performing local singularity analysis on PC1 and PC2,the obtained local anomalies reflected the local singularity spatial anomaly patterns related to Cu and Au mineralization in this area,which is an effective method for trapping ore-producing anomalies.(3)Furthermore,the composite anomaly decomposition of PC1 and PC2 was performed using the S-A method,and the screened anomalous and background fields reflect the ore-producing anomalies related to Cu and Au mineralization.This information is in agreement with known Cu and Au mineralization.(4)The geochemical anomalies with mineralization potential were obtained outside the known mineralization sites by integrating the information of oreproducing anomalies extracted by the local singularity and S-A methods,providing the theoretical basis and exploration direction for future exploration in the study area.

Application of pulsed chemical vapor deposition on the SiO_(2)-coated TiO_(2) production within a rotary reactor at room temperature

Pulsed chemical vapor deposition(P-CVD)is a promising technology for the surface modification of TiO_(2) particles.For the scale-up application of P-CVD,a custom-designed rotary reactor and corresponding coating process at room temperature was developed in the present work.The obtained SiO_(2)-coated TiO_(2) particles were characterized by various measures including high-resolution transmission electron microscope,Fourier transform infrared spectroscopy,X-ray diffraction,etc.The results illustrated that the SiO_(2) films with a thickness of(3.7±0.7)nm were successfully deposited onto the surface of TiO_(2) particles.According to the dye degradation tests and acid solubility measurement,the deposited film can effectively inhibit the photocatalytic activity and enhance the weatherability of the TiO_(2) particles.Zeta potential measurements showed that the SiO_(2)-coated TiO_(2) is possible to be stably dispersed in the pH range of 6.9–11.6.The coating process made the whiteness of TiO_(2) particles decreased slightly but still sufficient(97.3±0.1)for application.Furthermore,the properties of the TiO_(2) particles coated by PCVD were compared with the particles coated by traditional wet chemical deposition.It is shown that the P-CVD can produce thinner but denser films with better photoactivity suppression performance.The developed coating process within the rotary reactor was proved practically feasible and convenient for the scale-up production of SiO_(2)-coated TiO_(2) via P-CVD.

Screening and identification of functional bacterial attachment genes in aerobic granular sludge

The screening and identification of attachment genes is important to exploring the formation mechanism of biofilms at the gene level.It is helpful to the development of key culture technologies for aerobic granular sludge(AGS).In this study,genome-wide sequencing and gene editing were employed for the first time to investigate the effects and functions of attachment genes in AGS.With the help of whole-genome analysis,ten attachment genes were screened from thirteen genes,and the efficiency of gene screening was greatly improved.Then,two attachment genes were selected as examples to further confirm the gene functions by constructing gene-knockout recombinant mutants of Stenotrophomonas maltophilia;when the two attachment genes were knocked out,the attachment potential was reduced by 50.67%and 43.93%,respectively.The results provide a new theoretical principle and efficient method for the development of AGS from the perspective of attachment genes.

Influence of pore structure on thermal stress distribution inside coal particles during primary fragmentation

Thermal stress is an important reason of coal particle primary fragmentation,during which the role of pore structure is ambiguous.Thermal stress induced fragmentation experiments were conducted with low volatile coal/char particles,and the results show that the fragmentation severity enhances with increasing porosity.Various porous thermal stress models were developed with finite element method,and the influences of the pore shape,size,position and porosity on the thermal stress were discussed.The maximum thermal stress inside particle increases with pore curvature,the pore position affects the thermal stress more significantly at the particle center and surface.The expectation of the maximum tensile thermal stress linearly increases with porosity,making the particles with higher porosity easier to fragment,contrary to the conclusion deduced from the devolatilization theory.The obtained results are valuable for the analysis of different thermal processes concerning the thermal stresses of the solid feedstocks.

PCB CT Image Element Segmentation Model Optimizing the Semantic Perception of Connectivity Relationship

Computed Tomography(CT)is a commonly used technology in Printed Circuit Boards(PCB)non-destructive testing,and element segmentation of CT images is a key subsequent step.With the development of deep learning,researchers began to exploit the“pre-training and fine-tuning”training process for multi-element segmentation,reducing the time spent on manual annotation.However,the existing element segmentation model only focuses on the overall accuracy at the pixel level,ignoring whether the element connectivity relationship can be correctly identified.To this end,this paper proposes a PCB CT image element segmentation model optimizing the semantic perception of connectivity relationship(OSPC-seg).The overall training process adopts a“pre-training and fine-tuning”training process.A loss function that optimizes the semantic perception of circuit connectivity relationship(OSPC Loss)is designed from the aspect of alleviating the class imbalance problem and improving the correct connectivity rate.Also,the correct connectivity rate index(CCR)is proposed to evaluate the model’s connectivity relationship recognition capabilities.Experiments show that mIoU and CCR of OSPC-seg on our datasets are 90.1%and 97.0%,improved by 1.5%and 1.6%respectively compared with the baseline model.From visualization results,it can be seen that the segmentation performance of connection positions is significantly improved,which also demonstrates the effectiveness of OSPC-seg.

Size-resolved effective density of submicron particles during summertime in the rural atmosphere of Beijing, China

Particle density is an important physical property of atmospheric particles. The information on high time-resolution size-resolved particle density is essential for understanding the atmospheric physical and chemical aging processes of aerosols particles. In the present study, a centrifugal particle mass analyzer （CPMA） combined with a differential mobility analyzer （DMA） was deployed to determine the size-resolved effective density of 50 to 350 nm particles at a rural site of Beijing during summer 2016. The measured particle effective densities decreased with increasing particle sizes and ranged from 1.43 to 1.55 g/cm3, on average. The effective particle density distributions were dominated by a mode peaked at around 1.5 g/cm3 for 50 to 350 nm particles. Extra modes with peaks at 1.0, 0.8, and 0.6 g/cm3 for 150, 240, and 350 nm particles, which might be freshly emitted soot particles, were observed during intensive primary emissions episodes. The particle effective densities showed a diurnal variation pattern, with higher values during daytime. A case study showed that the effective density of Aitken mode particles during the new particle formation （NPF） event decreased considerably, indicating the significant contribution of organics to new particle growth.

Secondary organic aerosol formation from straw burning using an oxidation flow reactor

Herein,we use an oxidation flow reactor,Gothenburg:Potential Aerosol Mass(Go:PAM)reactor,to investigate the secondary organic aerosol(SOA)formation from wheat straw burning.Biomass burning emissions are exposed to high concentrations of hydroxyl radicals(OH)to simulate processes equivalent to atmospheric oxidation of 0-2.55 days.Primary volatile organic compounds(VOCs)were investigated,and particles were measured before and after the Go:PAM reactor.The influence of water content(i.e.5%and 11%)in wheat straw was also explored.Two burning stages,the flaming stage,and non-flaming stages,were identified.Primary particle emission factors(EFs)at a water content of 11%(~3.89 g/kg-fuel)are significantly higher than those at a water content of 5%(~2.26 g/kg-fuel)during the flaming stage.However,the water content showed no significant influence at the non-flaming stage.EFs of aromatics at a non-flaming stage(321.8±46.2 mg/kg-fuel)are larger than that at a flaming stage(130.9±37.1 mg/kg-fuel).The OA enhancement ratios increased with the increase in OH exposure at first and decreased with the additional increment of OH exposure.The maximum OA enhancement ratio is~12 during the non-flaming stages,which is much higher than~1.7 during the flaming stages.The mass spectrum of the primary wheat burning organic aerosols closely resembles that of resolved biomass burning organic aerosols(BBOA)based on measurements in ambient air.Our results show that large gap(0%-90%)still remains to estimate biomass burning SOA if only the oxidation of VOCs were included.

Isolation and characterization of a strain with high microbial attachment in aerobic granular sludge

Aerobic granule is a special microbial aggregate associated with biofilm structure.The formation of aerobic granular sludge is primarily depending on its bacterial community and relevant microbiological properties.In this experiment,a strain with high microbial attachment was isolated from aerobic granular sludge,and the detailed characteristics were examined.Its high attachment ability could reach 2.34(OD600 nm),while other low attachment values were only around 0.06-0.32,which indicated a big variation among the different bacteria.The strain exhibited a very special morphology with many fibric fingers under SEM observation.A distinctive behaviour was to form a spherical particle by themselves,which would be very beneficial for the formation and development of granular sludge.The EPS measurement showed that its PN content was higher than low attachment bacteria,and 3 DEEM confirmed that there were some different components.Based on the 16 S rRNA analysis,it was identified to mostly belong to Stenotrophomonas.Its augmentation to particle sludge cultivation demonstrated that the strain could significantly promote the formation of aerobic granule.Conclusively,it was strongly suggested that it might be used as a good and potential model strain or chassis organism for the aerobic granular sludge formation and development.